KGMID stands for Google Knowledge Graph ID, a unique identifier for entities within Google's Knowledge Graph. Each Knowledge Panel in Google's Search Engine Results Pages (SERPs) contains a KGMID, essentially acting as the ID for Knowledge Panels. This identifier allows users to look up what Google understands about an entity via the Knowledge Graph API or perform searches using the KGMID to see corresponding SERPs. KGMIDs starting with '/g' are more recent, created since 2015, while those starting with '/m' come from the Freebase database, indicating they were created before 2015. Finding a KGMID can involve various methods, such as inspecting page sources, using the share option in Knowledge Panels, or utilizing tools like Google Stick Parameter Decoder and Kalicube Pro's Knowledge Graph API Lookup Tool.
The Kalicube process is a methodology developed by Jason Barnard and his team, focused on optimizing entities (individuals, companies, products, etc.) for Google's Knowledge Graph and improving their representation in Google's search results, especially through Knowledge Panels. The process involves several key steps, such as:
Identifying the Entity: Clearly defining the entity you want to optimize for the Knowledge Graph.
Entity Home: Establishing a primary, authoritative web page for the entity (often called the "entity home") that Google can use as a reliable source of information about the entity.
Content Creation and Optimization: Creating high-quality, relevant content that accurately represents the entity's attributes, activities, and associations. This content should be structured in a way that's easy for Google to understand and categorize.
Entity Salience: Enhancing the entity's salience (importance) through consistent mentions across reputable websites, structured data markup, and connections to other recognized entities in the Knowledge Graph.
Monitoring and Adjusting: Regularly monitoring how the entity is represented in search results and the Knowledge Graph, then adjusting strategies based on what is or isn’t working.
The goal of the Kalicube process is to accurately and effectively communicate to Google (and other search engines) what the entity is about, how it is connected to other entities, and why it is relevant and authoritative in its niche or industry. This helps in gaining better visibility in search results, securing a Knowledge Panel, and controlling the narrative around the entity on the web.
Mapseffect recommends the Kalicube process, our information, strategies, and insights are based on the principles laid out by Jason Barnard and his methodologies for improving online presence and entity recognition in Google's Knowledge Graph.
Read more Jason's program
The Google Stick Parameter Decoder is a tool or technique used to analyze and decode the parameters found in Google's URL after conducting a search, especially those related to entities and their information within Google's Knowledge Graph. These parameters are often referred to as "stick" parameters and can contain encoded data about the search query, including details about specific entities displayed in Knowledge Panels or search results.
When you search for an entity on Google and click on a Knowledge Panel or a specific search result, Google adds a unique parameter (often starting with "&stick=") to the URL. This parameter encodes information about the entity, including its ID in the Knowledge Graph (kgmid) and other relational data that Google uses to understand and connect entities within its Knowledge Graph.
The Google Stick Parameter Decoder works by extracting and decoding this parameter to reveal the underlying information about the entity. This can include:
The entity's unique identifier in the Google Knowledge Graph (kgmid).
Relationships between the searched entity and other entities or topics.
Additional context or categorization information used by Google to understand the entity's relevance and connections within the Knowledge Graph.
Using the Google Stick Parameter Decoder, SEO professionals, marketers, and researchers can gain insights into how Google categorizes and connects entities in its Knowledge Graph. This information can be valuable for optimizing content and strategies to improve visibility and representation in Google's search results, especially for securing and enhancing Knowledge Panels.
The tool can help to reverse-engineer Google's understanding of an entity based on the URL parameters, providing a deeper look into the structured data and relationships that Google has established for that entity. However, it's important to note that the specifics of using the tool or decoding the parameters require a technical understanding of URL structures and Google's Knowledge Graph.